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008			200717t20192019my ab||fram|| 000 0 eng d
020			_aTHE0008779(Local) _qhardback
040			_aUMP _beng _cUMP _erda
090			_aFKASA .A373 2019 r Bc.
100	0		_aSiti Nur’aisyah Jamalludin, _eauthor.
245	1	4	_aThe best interpolation method for wind speed by using GIS / _cSiti Nur’aisyah Jamalludin
264		1	_aKuantan, Pahang : _bUMP, _c2019
264		4	_c© 2019
300			_axi, 55 pages : _billustrations, maps (some color) ; _c30 cm. + _e1 CD-ROM
336			_atext _2rdacontent
336			_atext _2rdacontent
337			_aunmediated _2rdamedia
337			_acomputer _2rdamedia
338			_avolume _2rdacarrier
338			_acomputer disc _2rdacarrier
347			_atext file _bPDF _2rda
500			_aFaculty of Civil Engineering and Earth Resources
502			_aProject Paper (Bachelors of Civil Engineering) -- Universiti Malaysia Pahang – 2019
504			_aIncludes bibliographical references
520	3		_aThe wind speed had played the very vital role in weather forest because wind hazard damages increased every year. When estimating the wind speed is important to use the interpolation method especially the location do not has a weather forest or meteorological stations. In this research, the three different method of spatial interpolation which was Inverse Distance Weighting (IDW), Spline and Kriging were compared to determine the suitability for estimating wind speed. Therefore, the all methods were evaluated with the regression analysis and correlation coefficient analysis. Based on the results obtained, Kriging was shown the more suitable to estimate the wind speed by followed the other methods which are IDW and Spline. Future studies with more data collected, denser sample points and different cases can be carried out to obtain a more accurate result.
610	2	0	_aFaculty of Civil Engineering and Earth Resources _xDisertations
650		0	_aUniversities and colleges _xDisertations
650		0	_aTheses
942			_2lcc _cPSM